Method and system for efficiently verifying optical proximity correction

ABSTRACT

A method of verifying optical proximity correction includes the steps of generating first mask pattern data from design data under first condition, generating first corrected pattern data by applying optical proximity correction to the first mask pattern data, generating second mask pattern data from the design data under second condition, generating second corrected pattern data by applying optical proximity correction to the second mask pattern data, and comparing the first corrected pattern data and the second corrected pattern data to check whether the first corrected pattern data and the second corrected pattern data match.

CROSS-REFERENCE TO RELATED APPLICATION

This is a continuation of International Application No.PCT/JP2003/005523, filed on Apr. 30, 2003, the entire contents of whichare hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to methods, programs, andsystems for verifying mask pattern data processes when generating maskpatterns, and particularly relates to a method, program, and system forverifying an optical proximity correction process.

2. Description of the Related Art

In manufacturing of semiconductor devices, the pattern shape of a maskpattern is printed on a wafer by use of an optical transfer apparatus.As the miniaturization of semiconductor devices is further advanced,adjacent patterns may come in contact with each other because of anoptical proximity effect. Further, corners of patterns may be rounded,and lines may become thinner and severed. By estimating such patterndeformation, the pattern data is processed such as to cancel or mitigatethe deformation, thereby performing a correction process for ensuringthat desired pattern shape is properly formed on the wafer. This isreferred to as an optical proximity correction process.

The optical proximity correction process generates an aid pattern formask pattern data in order to attain a desired wafer-transfer image bycorrecting the pattern on the reticle. Conventional pattern correctionmethods set rules with respect to the patters for correcting designdata, and generate an aid pattern for reticle pattern data based on therules for generating corrected patterns.

In order to check the pattern correction process as to whether it issatisfactory or unsatisfactory, a corrected pattern is generated for asimple predetermined test pattern. Visual inspection of this correctedpattern may then be carried out to see whether a desired pattern hasbeen obtained. When the data is complex and its size is massive as inthe case of an actual product, it is practically impossible to conductvisual inspection of the corrected pattern. Even when tools are used forverification, the results may not match each other, resulting in a largenumber of discrepancies, which makes the verification difficult.

[Patent Document 1] Japanese Patent Application Publication 2002-107908

Accordingly, there is a need for a verification method that canefficiently check whether optical proximity correction is properlyworking during the process of generating mask pattern data.

SUMMARY OF THE INVENTION

It is a general object of the present invention to provide averification method that substantially obviates one or more problemscaused by the limitations and disadvantages of the related art.

Features and advantages of the present invention will be presented inthe description which follows, and in part will become apparent from thedescription and the accompanying drawings, or may be learned by practiceof the invention according to the teachings provided in the description.Objects as well as other features and advantages of the presentinvention will be realized and attained by verification methodparticularly pointed out in the specification in such full, clear,concise, and exact terms as to enable a person having ordinary skill inthe art to practice the invention.

To achieve these and other advantages in accordance with the purpose ofthe invention, the invention provides a method of verifying opticalproximity correction, which includes the steps of generating first maskpattern data from design data under first condition, generating firstcorrected pattern data by applying optical proximity correction to thefirst mask pattern data, generating second mask pattern data from thedesign data under second condition, generating second corrected patterndata by applying optical proximity correction to the second mask patterndata, and comparing the first corrected pattern data and the secondcorrected pattern data to check whether the first corrected pattern dataand the second corrected pattern data match.

According to the method described above, if a match between the two dataitems is found based on the check as to whether the two data itemsmatch, it is ascertained that the optical proximity correction is freefrom errors in terms of handling and processing of figures, and that aproper correction process is being performed. If there is a mismatchbetween the two data items, on the other hand, the optical proximitycorrection is modified to provide for appropriate optical proximitycorrection.

Further, the present invention provides a memory medium having a programembodied therein for causing a computer to perform the steps of theabove-noted method of verifying optical proximity correction, and alsoprovide a system that performs the method of verifying optical proximitycorrection.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects and further features of the present invention will beapparent from the following detailed description when read inconjunction with the accompanying drawings, in which:

FIG. 1 is a flowchart showing a process of checking the properness ofoptical proximity correction by generating corrected pattern datathrough changes of angles;

FIG. 2 is a drawing for explaining a verification process in the case ofrotation;

FIG. 3 is a drawing showing an example of the data structure of maskpattern data;

FIG. 4 is a drawing showing an example of the data structure of maskpattern data in a case where mask pattern data is rotated;

FIG. 5 is a flowchart of a process of checking the properness of opticalproximity correction by generating corrected pattern data by changingthe position of division;

FIG. 6 is a drawing showing an example of the data structure of maskpattern data in a case where the way the mask pattern data is dividedinto areas is changed;

FIG. 7 is a drawing for explaining a verification process in a case inwhich rotation and a change in the position of division are integrated;and

FIG. 8 is a drawing showing the construction of an apparatus forperforming a method of verifying optical proximity correction accordingto the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following, embodiments of the present invention will be describedwith reference to the accompanying drawings.

The present invention applies optical proximity correction to the firstmask pattern data obtained from design data, thereby generating firstcorrected pattern data. Optical proximity correction is further appliedto the second mask pattern data that is obtained from the same designdata under different conditions, thereby generating second correctedpattern data. The first corrected pattern data and the second correctedpattern data are compared to check whether they match. If the comparisonfinds that these patterns match, then, it is properly ascertained thatthe optical proximity correction process is free from errors in terms ofhandling and processing of figures, and that a proper correction processis being performed.

A specific example of generating the second corrected pattern data underdifferent conditions may be a method that rotates first mask patterndata a predetermined angle to generate second mask pattern data, andapplies optical proximity correction to the second mask pattern data,followed by rotating the second mask pattern data in the reversedirection to place it back at the original angle, thereby obtaining thesecond corrected pattern data. Another specific example may be a methodthat is used in a case where mask pattern data is divided andrepresented as data comprised of a plurality of fields. This methoddivides the mask pattern data into a plurality of fields at positionsdifferent from those used for generating the first mask pattern data,thereby generating second mask pattern data. As a method of shifting thedividing positions, the direction in which division is made may bechanged, or the width of a process grid may be changed to modify thepitches of division. Positions at which division is made may also beshifted.

FIG. 1 is a flowchart showing a process of checking the properness ofoptical proximity correction by generating corrected pattern datathrough changes of angles.

At step ST1 of FIG. 1, design data 10 is converted into mask patterndata 11. In doing so, data processing information 21 is referred to,thereby performing the conversion under conditions specified in thisinformation. The data processing information 21 includes layerinformation about pattern layers, top-fig information about theuppermost layer pattern, sizing information about the size of patterns,divided area information about the areas by which a pattern is dividedinto a plurality of fields.

At step ST2, optical proximity correction is applied to the mask patterndata 11, thereby generating corrected mask pattern data (first correctedpattern data) 12. In so doing, correction information 22 is referred to,thereby applying optical proximity correction under conditions specifiedin this information. The correction information 22 defines rules ofoptical proximity correction.

In the optical proximity correction described above, the mask patterndata is recognized as a geometrical polygon figure. Based on suchrecognition, processes such as searching for pattern width and space,determination of correction values, and generation of a corrected figureare performed. Most of these processes are carried out by manipulatingthe coordinates of the vertexes of the figure. The manipulation ofvertexes is generally performed for the X coordinate and for the Ycoordinate separately. Each side of the figure is classified into thehorizontal direction, vertical direction, and diagonal directionaccording to predetermined rules, and is manipulated separately. When asingle rectangle is to be corrected, for example, the four sides arerecognized as four vectors extending counterclockwise, and the Xcoordinates and Y coordinates of the vectors parallel to each other aremodified.

At step ST3, the mask pattern data 11 is subjected to rotation A,thereby generating mask pattern data 13.

At step ST4, optical proximity correction is applied to the mask patterndata 13 to generate corrected mask pattern data (corrected pattern data)14. In so doing, the correction information 22 is referred to, therebyperforming optical proximity correction under conditions specified inthis information. The correction information 22 defines rules of opticalproximity. correction, and is the same as the correction information 22used at step ST2.

At step ST5, the mask pattern data (corrected pattern data) 14 issubjected to rotation B, thereby generating mask pattern data (secondcorrected pattern data) 15. Compared with the rotation A, the rotation Brotates the pattern data the same angle in the reverse direction.Accordingly, the mask pattern data (second corrected pattern data) 15 isplaced at the same angle as the mask pattern data 11.

At step ST6, the mask pattern data (first corrected pattern data) 12 andthe mask pattern data (second corrected pattern data) 15 are comparedwith each other through data comparison by the computer to check whetherthese data items match. If the comparison finds that these data itemsmatch each other, the mask pattern data 12 is ascertained to be properdata, which is usable for the creation of a mask. If the comparisonfinds that these data items do not match, the optical proximitycorrection is ascertained to be inappropriate. Since it is found thatthere is a problem with the optical proximity correction, the opticalproximity correction is fixed by use of predetermined tools at step ST7.

FIG. 2 is a drawing for explaining a verification process in the case ofrotation. FIG. 2 illustrates a case in which a rotation angle is 90degrees.

Starting from the top left corner in FIG. 2 and moving counterclockwise,the mask pattern data 11 is turned into vectors, thereby generatingvector data 11A. Correction process is applied to the vector data 11Aevenly with respect to the X direction and with respect to the Ydirection so as to generate corrected data. The mask pattern data (firstcorrected pattern data) 12 is thus obtained.

Starting from the top left corner in FIG. 2 and moving clockwise, themask pattern data 11 is rotated 90 degrees to generate the mask patterndata 13. The mask pattern data 13 is then turned into vectors togenerate vector data 13A. Correction process is applied to the vectordata 13A evenly with respect to the X direction and with respect to theY direction so as to generate corrected data. The mask pattern data(corrected pattern data) 14 is thus obtained. Further, the mask patterndata (corrected pattern data) 14 is rotated by −90 degrees to generatethe mask pattern data (second corrected pattern data) 15.

Lastly, the mask pattern data (first corrected pattern data) 12 and themask pattern data (second corrected pattern data) 15 are compared witheach other to check whether they match, thereby verifying the opticalproximity correction. In the example shown in FIG. 2, correction in theY direction has a problem, for example. Despite the fact that correctionis applied evenly with respect to the X direction and with respect tothe Y direction, therefore, correction is not sufficient in the Ydirection. As a result, the mask pattern data (first corrected patterndata) 12 is shorter in the Y direction than properly corrected size, andthe mask pattern data (second corrected pattern data) 15 is shorter inthe X direction than properly corrected size. In this manner, thecomparison of corrected pattern data makes it possible to find that thecorrection process has a problem with respect to the Y direction.

FIG. 3 is a drawing showing an example of the data structure of maskpattern data.

As shown in FIG. 3, the design data 10 is subjected to mask dataconversion (i.e., the process of ST1 in FIG. 1). This generates the maskpattern data 11. It should be noted that the design data 10 and the maskpattern data 11 illustrated in FIG. 3 are not data themselves, but arethe visualized images of the mask pattern. The mask pattern data 11 isdivided into four fields FIELDa through FIELDd, and is divided into sixsub-fields SUB-FIELD1 through SUB-FIELD6.

At the bottom of FIG. 3, an example of the data structure of the maskpattern data 11 is illustrated as header information 31 and real datainformation 32. The header information 31 is a header, only one of whichis provided for a single item of the mask pattern data 11. The headerinformation 31 indicates the file name of the data file, the size of aprocess grid, and the start address of each field. In the example ofFIG. 3, the file name of the data file is “Aaa.data”, and the size of aprocess grid “0.01 micron”. Further, the start addresses of FIELDathrough FIELDd are “0001”, “0A00”, “0B01”, and “0F01”, respectively.

The real data information 32 stores the mask pattern data correspondingto the individual sub-fields of a given field, starting from the startaddress of this given field as indicated in the header information 31.For example, the start address of FIELDa is “0001”. Starting from theaddress “0001”, therefore, the mask pattern data of the SUB-FIELD1 ofFIELDa, the mask pattern data of the SUB-FIELD2 of FIELDa, the maskpattern data of the SUB-FIELD3 of FIELDa, and so on are stored. The maskpattern data of the SUB-FIELD1 of FIELDa, for example, corresponds tothe mask pattern data contained in a divided area 33 located at the topleft corner of the visualized image of the mask pattern data 11 shown inFIG. 3.

FIG. 4 is a drawing showing an example of the data structure of maskpattern data in a case where mask pattern data is rotated.

As shown in FIG. 4, the design data 10 is subjected to mask pattern dataconversion (inclusive of rotation), thereby generating the mask patterndata 13. In the examples of FIG. 1 and FIG. 2, the mask pattern data 13is generated from the mask pattern data 11. As shown in FIG. 4, the maskpattern data 13 as rotated may be generated directly from the designdata 10. The mask pattern data 13 is divided by the four fields FIELDathrough FIELDd and the six sub-fields SUB-FIELD1 through SUB-FIELD6.

The header information 31 of the mask pattern data 13 is the same as theheader information 31 shown in FIG. 3. On the other hand, real datainformation 42 has data contents completely different from those of thereal data information 32 shown in FIG. 3. This is because the maskpattern data 13 is rotated 90 degrees relative to the mask pattern data11, so that the mask pattern data contained in each sub-field completelydiffers between the mask pattern data 11 and the mask pattern data 13.

Through such rotation process, it is possible to obtain the mask patterndata 11 and the mask pattern data 13 that are completely different fromeach other as far as data contents are concerned, despite the fact thatthe substance as a mask is the same. The mask pattern data 11 and themask pattern data 13 are subjected to optical proximity correction,thereby detecting an error in the optical proximity correction, aspreviously described.

FIG. 5 is a flowchart of a process of checking the properness of opticalproximity correction by generating corrected pattern data by changingthe position of division. FIG. 5 shows a portion corresponding to thegeneration of the mask pattern data (first corrected pattern data) 12 asshown in FIG. 1 and the comparison-purpose mask pattern data (secondcorrected pattern data).

At step ST1, conversion conditions are selected based on data processinginformation 21A. The data processing information 21A includes layerinformation about pattern layers, top-fig information about theuppermost layer pattern, sizing information about the size of patterns,divided area information about the areas by which a pattern is dividedinto a plurality of fields. In the process shown in FIG. 5, mask patterndata is generated by use of area divisions different from those for themask pattern data 11 shown in FIG. 1. Because of this, the divided areainformation of the data processing information 21A has differentsettings than the divided area information of the data processinginformation 21 of FIG. 1.

At step ST2, the design data 10 is converted into mask pattern data 16.The mask pattern data 16 is the same as the mask pattern data 11 of FIG.1 as far as the substance as a mask is concerned. Since the way thefields and sub-fields are arranged through division are different, thesetwo data items differ from each other completely as data contents areconcerned.

At step ST4, optical proximity correction is applied to the mask patterndata 16 to generate corrected mask pattern data (second correctedpattern data) 17. In so doing, the correction information 22 is referredto, thereby performing optical proximity correction under conditionsspecified in this information. The correction information 22 definesrules of optical proximity correction, and is the same as the correctioninformation 22 used at step ST2 of FIG. 1.

The mask pattern data (second corrected pattern data) 17 obtained inthis manner is compared with the mask pattern data (first correctedpattern data) 12 of FIG. 1 through data comparison by the computer,thereby checking whether they match. If the comparison finds that thesetwo data items match, the mask pattern data 12 is regarded as properdata, which is usable for mask generation. If the comparison finds thatthese two data items do not match, it is ascertained that the maskpattern data 12 is not proper, and that the optical proximity correctionhas a problem. In this case, predetermined tools are used to fix theoptical proximity correction.

FIG. 6 is a drawing showing an example of the data structure of maskpattern data in a case where the way the mask pattern data is dividedinto areas is changed.

In FIG. 6, the mask pattern data 16 is divided by five fields FIELDathrough FIELDe and seven sub-fields SUB-FIELD1 through SUB-FIELD7.Compared with the mask pattern data 11 shown in FIG. 3, the number offields and the number of sub-fields are increased by 1, respectively.This is because the pitches of fields and sub-fields are set shorter, sothat the position of division differs between the mask pattern data 11of FIG. 3 and the mask pattern data 16 of FIG. 6.

Header information 51 of the mask pattern data 16 differs from theheader information 31 shown in FIG. 3. The interval of a process grid isset to 0.008 micron, which is shorter than 0.01 micron shown in theexample of FIG. 3. This provides shorter pitches for the fields andsub-fields. As a result, the field FIELDe is added as a fifth field.

Real data information 52 is inevitably different from the real datainformation 32 of FIG. 3 as far as the data contents are concerned. Thisis because the pitches of fields and sub-fields are different betweenthe mask pattern data 11 and the mask pattern data 16, and so are thepositions where division is made.

Through such process that shifts the positions where division is made,it is possible to obtain the mask pattern data 11 and the mask patterndata 16 that are completely different from each other as far as datacontents are concerned, despite the fact that the substance as a mask isthe same. The mask pattern data 11 and the mask pattern data 16 aresubjected to optical proximity correction, thereby detecting an error inthe optical proximity correction, in the same manner as previouslydescribed.

The above description has been given by treating rotation and a changein the position of division as separate, independent embodiments.Alternatively, rotation and a change in the position of division may beintegrated and performed together. In the following, a description willbe given of such an embodiment.

FIG. 7 is a drawing for explaining a verification process in a case inwhich rotation and a change in the position of division are integrated.

As shown at the top left corner of FIG. 7, two fields 61 and 62 areprovided for mask pattern data 71. In the current state, the maskpattern data 71 is not divided into the fields 61 and 62. The fields 61and 62 are illustrated here for the sake of convenience of explanation,and are simply the divided areas having no substance that aresuperimposed for illustration on the position of the mask pattern data71.

Starting from the top left corner and tracing the arrowscounterclockwise, the mask pattern data 71 is first rotated 90 degreesto generate mask pattern data 72. The mask pattern data 72 is thendivided by the fields 61 and 62, and is represented as the data of theindividual fields. Further, spaces 81 and 82 between the individualitems of the mask pattern data 72 are identified. Taking these spacesinto account, optical proximity correction is applied, thereby obtainingcorrected mask pattern data 73. The corrected mask pattern data 73 isthen rotated −90 degrees, which generates mask pattern data (firstcorrected pattern data) 74.

Starting from the top left corner of FIG. 7 and tracing the arrowsclockwise, the mask pattern data 71 is first divided by the fields 61and 62, and is represented as the data of the individual fields. As canbe seen from the drawing, the position where the mask pattern data 71 isdivided into the fields 61 and 62 is different from the position wherethe mask pattern data 72 as rotated 90 degrees is divided into thefields 61 and 62 as described above. This is because the mask patterndata is rotated relative to the fields 61 and 62. With respect to themask pattern data 71 obtained in this manner, spaces 91 and 92 betweenthe individual elements are identified. By taking these spaces intoaccount, optical proximity correction is applied, thereby generatingmask pattern data (second corrected pattern data) 75.

Lastly, the mask pattern data (first corrected pattern data) 74 and themask pattern data (second corrected pattern data) 75 are compared witheach other to check whether they match. This serves to verify theoptical proximity correction. When the mask pattern data is divided intothe fields 61 and 62 as shown in this example, it is necessary torecognize the presence of patterns close to the boundaries of the fieldswhen optical proximity correction is applied. Since the patterns of theindividual fields are treated as separate data on a field-by-fieldbasis, it is likely to have a problem in that patterns are not properlyrecognized through program errors near the boundaries. In the exampledescribed above, the mask pattern data is rotated 90 degrees relative tothe fields 61 and 62 so as to change the way the pattern is divided,thereby making it possible to detect such errors.

FIG. 8 is a drawing showing the construction of an apparatus forperforming a method of verifying optical proximity correction accordingto the present invention.

As shown in FIG. 8, the apparatus for performing a method of verifyingoptical proximity correction according to the present invention isimplemented as a computer such as a personal computer or an engineeringworkstation. The apparatus shown in FIG. 8 includes a computer 510, adisplay apparatus 520 connected to the computer 510, a communicationapparatus 523, and an input apparatus. The input apparatus includes akeyboard 521 and a mouse 522. The computer 510 includes a CPU 511, a RAM512, a ROM 513, a secondary storage device 514 such as a hard disk, aremovable-medium storage device 515, and an interface 516.

The keyboard 521 and mouse 522 provide user interface, and receivevarious commands for operating the computer 510 and user responsesresponding to data requests or the like. The display apparatus 520displays the results of processing by the computer 510, and furtherdisplays various data that makes it possible for the user to communicatewith the computer 510. The communication apparatus 523 provides forcommunication with a remote cite, and may be comprised of a modem,network interface, or the like.

The method of verifying optical proximity correction according to thepresent invention is provided as a computer program executable by thecomputer 510. This computer program is stored in a memory medium M thatis mountable to the removable-medium storage device 515. The computerprogram is loaded to the RAM 512 or the secondary storage device 514from the memory medium M through the removable-medium storage device515. Alternatively, the computer program may be stored in a remotememory medium (not shown), and is loaded to the RAM 512 or the secondarystorage device 514 from the remote memory medium through thecommunication apparatus 523 and the interface 516.

Upon user instruction for program execution entered through the keyboard521 and/or the mouse 522, the CPU 511 loads the program to the RAM 512from the memory medium M, the remote memory medium, or the secondarystorage device 514. The CPU 511 executes the program loaded to the RAM512 by use of a free space of the RAM 512 as a work area, and continuesprocessing while communicating with the user as a need arises. The ROM513 stores therein control programs for the purpose of controlling basicoperations of the computer 510.

Execution of the computer program makes it possible to perform themethod of verifying optical proximity correction as described in theabove embodiments. The computer environment for the execution of themethod of verifying optical proximity correction is the opticalproximity correction verifying system or optical proximity correctionverifying apparatus.

Further, the present invention is not limited to these embodiments, butvarious variations and modifications may be made without departing fromthe scope of the present invention.

1. A method of verifying optical proximity correction, comprising thesteps of: generating first mask pattern data from design data underfirst condition; generating first corrected pattern data by applyingoptical proximity correction to the first mask pattern data; generatingsecond mask pattern data from said design data under second condition;generating second corrected pattern data by applying optical proximitycorrection to the second mask pattern data; and comparing the firstcorrected pattern data and the second corrected pattern data to checkwhether the first corrected pattern data and the second correctedpattern data match.
 2. The method as claimed in claim 1, furthercomprising a step of modifying the optical proximity correction inresponse to a mismatch between the first corrected pattern data and thesecond corrected pattern data.
 3. The method as claimed in claim 1,wherein the step of generating first mask pattern data generates thefirst mask pattern data without rotating the design data, and the stepof generating second mask pattern data generates the second mask patterndata by rotating the design data a predetermined angle in apredetermined direction, and wherein the step of generating secondcorrected pattern data generates the second corrected pattern data byrotating the second mask pattern data the predetermined angle in adirection opposite the predetermined direction after the opticalproximity correction is applied to the second mask pattern data.
 4. Themethod as claimed in claim 3, wherein the predetermined angle is aninteger multiple of 90 degrees.
 5. The method as claimed in claim 1,wherein the step of generating first mask pattern data generates thefirst mask pattern data by dividing the design data into firstpredetermined areas, and the step of generating second mask pattern datagenerates the second mask pattern data by dividing the design data intosecond predetermined areas different from the first predetermined areas.6. The method as claimed in claim 1, wherein the step of generatingfirst mask pattern data defines the first predetermined areas by a firstprocess grid, and the step of generating second mask pattern datadefines the second predetermined areas by a second process griddifferent from a first process grid.
 7. The method as claimed in claim1, wherein the step of generating first mask pattern data generates thefirst mask pattern data by dividing the design data into predeterminedareas without rotating the design data, and the step of generatingsecond mask pattern data generates the second mask pattern data byrotating the design data a predetermined angle in a predetermineddirection and by dividing the rotated design data into the predeterminedareas, and wherein the step of generating second corrected pattern datagenerates the second corrected pattern data by rotating the second maskpattern data the predetermined angle in a direction opposite thepredetermined direction after the optical proximity correction isapplied to the second mask pattern data.
 8. The method as claimed inclaim 7, wherein the predetermined angle is an integer multiple of 90degrees.
 9. A record medium having a program embodied therein forcausing a computer to verify optical proximity correction, said programcausing the computer to execute steps comprising: generating first maskpattern data from design data under first condition; generating firstcorrected pattern data by applying optical proximity correction to thefirst mask pattern data; generating second mask pattern data from saiddesign data under second condition; generating second corrected patterndata by applying optical proximity correction to the second mask patterndata; and comparing the first corrected pattern data and the secondcorrected pattern data to check whether the first corrected pattern dataand the second corrected pattern data match.
 10. A system for verifyingoptical proximity correction, comprising: a unit configured to generatefirst mask pattern data from design data under first condition; a unitconfigured to generate first corrected pattern data by applying opticalproximity correction to the first mask pattern data; a unit configuredto generate second mask pattern data from said design data under secondcondition; a unit configured to generate second corrected pattern databy applying optical proximity correction to the second mask patterndata; and a unit configured to compare the first corrected pattern dataand the second corrected pattern data to check whether the firstcorrected pattern data and the second corrected pattern data match.